1. Field of the Invention
The present invention relates generally to systems and methods of identifying circadian rhythm related variations of human medical attributes, and more specifically to utilizing Lissajous analysis techniques for identifying cardiac function attributes that present circadian variations, and further utilizing the identified cardiac function attributes to forecast relative risks of sudden cardiac death (SCD).
2. Related Art
Among the more vexing issues still confronting medical professionals attempting to treat people with cardiac health issues, despite a number of substantial advances in both their diagnosis as well as their treatment, are difficulties in predicting exactly which patients are most susceptible to certain catastrophic negative outcomes, such as sudden cardiac death. Almost half a million people die in the U.S.A. suddenly each year from lethal electric rhythms of the heart, and many of these deaths could be prevented by surgically implanted defibrillators, if high risk patients can be accurately identified in advance. In the USA alone, tens of thousands of cardiac defibrillators are surgically implanted annually to prevent sudden cardiac death, but as many as 90% of them are unnecessary. Inadequate knowledge about what specific patient characteristics presage sudden cardiac death has led to establishment of a low threshold criterion for defibrillator implantation, namely, a left ventricular ejection fraction <30%. Per patient costs for initial implantation are $29,000˜$55,000, which would result in an estimated annual cost of $5 billion if all American patients with ejection fraction <30% were to receive a defibrillator. To save one life using this criterion, it would reportedly be necessary to treat 11 patients, so that 10 out of 11 patients would receive defibrillators that would never be deployed, or worse, would not save their lives in spite of the pain, risk, and cost of the implantation. Currently, relatively crude heart pump function criterion are used to make most defibrillator implantation decisions, and it would be advantageous to determine electrically-based heart measurement characteristics capable of enhancing the heart pump function criteria when making these decisions. Better criteria would reduce health care costs as well as the physical and psychological burden borne by patients who unnecessarily receive defibrillators based on the current criterion. One of the more effective modern approaches to averting SCD in patients involves the implantation of cardiac defibrillators. The implanted defibrillators are relatively effective in averting the most negative consequences when a patient's heart fibrillates, but they are not without costs and drawbacks because their implanting involves major surgery with its attendant risks, discomforts, and expenses. Additionally, hereto now, it has not been possible to target those in critical need more accurately than the aforementioned one in ten. This inefficiency is because cardiologists have only crude criteria for predicting which patients' hearts are likely to fibrillate.
The crux of the issue, then, is the need for a reliable, accurate stratifier of patients' risk of SCD. The investigation of heart function manifestations represented in electrocardiograph recordings has provided substantial insights into the functioning of the human heart. The electrocardiographic QT interval (denoted herein as QT) has a long history of study as a risk stratifier, because physicians recognized early on that a long QT predisposes patients to potentially lethal rhythms of the heart called ventricular tachycardia, especially torsade de pointes. QT is also known to increase before the onset of ventricular tachyarrhythmias during acute myocardial ischemia. However, unlike most electrocardiographic measures with clear numerical limits on what is considered normal, QT has a nonlinear dependence on heart rate, and the raw QT by itself cannot be classified as being longer or shorter than normal, without accompanying heart rate information; additionally, besides its value depending on heart rate, the QT is also affected by cardiac sympathetic and vagal nerve activity. QT has also been examined as a possible predictor of ventricular fibrillation, but so far, predictions of SCD based on conventional QT characterizations, such as its reduction to a single value using heart rate correction formulas, have failed to dramatically reduce this inefficiency. The slope of QT plotted against the electrocardiographic RR interval (denoted herein as RR; essentially equivalent to the inverse of heart rate) has been found to be strongly correlated with fibrillation in animal and theoretical studies, which has led to recent studies investigating this slope for risk prediction value in humans.
Bazett's formula, first published in 1920, takes a QT and the prevailing heart rate, and produces a single value called rate-corrected QT interval (QTc). Therefore, QTc was one of the earliest QT based risk predictors studied. Despite some compelling evidence that long QTc after myocardial infarction [Schwartz 1978; Ahnve 1984] or in chronic ischemic heart disease [Puddu 1986] predicts SCD, large prospectively designed studies in patients surviving myocardial infarction [Pohjola-Sintonen 1986, Wheelan 1986] and the Framingham Heart Study [Goldberg 1991] have failed to verify the utility of QTc as a risk predictor. The focus of QT based studies then shifted to other measures of QT, such as 24 hour QT variability [Homs 1997], QT dispersion [Molnar 1997], and day-night difference in QT [Yi 1998]. The study of these parameters helped to advance knowledge about QT dynamics, but yielded little with respect to risk prediction. More recently, the QT/RR slope, which is the slope of the QT plotted against the preceding RR interval (time between two QRS peaks) has been attracting interest, and has been investigated by three groups as a risk predictor. After finding that patients with inducible ventricular tachycardia had greater QT/RR slope [Extramiana 1999a], the group led by P. Coumel and P. Maison-Blanche studied QT/RR slope in the EMIAT database (European Myocardial Infarction Amiodarone Trial). In this trial, patients were followed for a mean of 21 months. Ambulatory electrocardiographs, usually referred to as Holter monitors after their inventor, Dr. Norman J. Holter, are portable devices for continuously monitoring the electrical activity of the heart for extended periods, the standard duration of which is 24 hours, and in circumstances that are not replicable in the laboratory. Its extended recording period is sometimes useful for observing occasional cardiac arrhythmias that would be difficult to identify in a shorter period of time. Comparison of Holter (24 hour) electrocardiographic records from 118 cardiac death patients and 118 matched survivors showed that patients who died from SCD had a steeper QT/RR slope in the 2 hours around the morning heart rate acceleration period than patients who died non-sudden deaths [Milliez 2005]. QT/RR slope was the only independent predictor of whether a cardiac death was sudden or non-sudden in a multivariate model that included no electrocardiographic predictors, except for number of ventricular premature complexes and heart rate. Another group studied QT/RR slope using a different calculation technique in the GREPI database (Groupe d'Etude du Pronostic de l'Infarctus du Myocarde). They used 265 Holter records from recent infarction patients, who were followed for a mean of 81 months. Of electrocardiographic predictors, steep daytime (9 AM-9 PM) QT/RR slope was found to be the strongest predictor of SCD followed by night time heart rate and the SDANN (Standard Deviation of Average Normal RR intervals) measure of heart rate variability [Chevalier 2003]. In contrast to these two post-infarction studies, Smetana et al studied QT/RR slope in 866 Holter records from the same EMIAT database as the Coumel Maison-Blanche group, but using a different technique for QT/RR slope calculation and different statistical design, and reached the completely opposite conclusion that flatter, rather than steeper QT/RR slope predicted SCD [Smetana 2004]. These studies suggest that QT/RR slope calculation methods need to be grouped according to scientifically grounded criteria, then compared in the same cohort of patients. These studies have also failed to assess independence of QT/RR slope as a predictor of SCD in multivariate analyses that include newer, more potent electrocardiographic predictors of cardiac mortality and SCD, such as heart rate turbulence [reviewed in Watanabe 2004] and deceleration capacity [Bauer 2006a].
The presence of hysteresis between heart rate change and corresponding QT change is a significant difficulty that arises when one tries to compute QT/RR slope. In the field of cardiac function research, the expression hysteresis is used to denote two types of hysteresis, a first type that refers to the variable relatively short timescale lag between changes in RR and corresponding changes in QT (generally measurable in seconds or minutes), and a second type which refers to the relatively long timescale lag (generally measurable in hours) between RR and QT that is related to circadian variations in autonomic tone. To preclude uncertainties related to distinguishing between these two forms of hysteresis, the expression hysteresisVAR will be utilized herein to denote the short term RR change instigated type of hysteresis, and the expression hysteresisCIRC will be utilized herein to denote the longer term circadian related hysteresis. Describing hysteresisVAR first: after an abrupt change in heart rate, QT takes time to attain its new value [Arnold 1982, Lau 1988]. For example, if heart rate were to change rapidly from 60 bpm to 100 bpm, QT during the first minute at 100 bpm would be greater than QT that had been given time to shorten to a steady state value. Likewise, if heart rate were suddenly switched back to 60 bpm, the QT during the first minute back at 60 bpm would be shorter than QT that had been given time to lengthen to the steady state value at 60 bpm. This temporal lag causes QT to be different at identical heart rates, depending on whether you are measuring a transient value, or the steady state value. This phenomenon is called QT hysteresis in the literature, and can be quantified as the difference between QT values at a pre-determined heart rate [Lewis 2006]. The presence of such hysteresisVAR produces a cloud of points when QT is plotted against RR, because there isn't a single QT value for a given RR, and hysteresisVAR reduces both the slope value and the r squared value of the regression. Describing hysteresisCIRC next: multiple studies have shown that QT is greater at night than during the daytime at the same heart rate [Browne 1983a, Bexton 1986, Cinca 1986, Murakawa 1992, Anselme 1996, Badilini 1999]. This is attributed to the predominance of vagal autonomic nerve activity at night. Murakawa et al specifically correlated the day-night difference in QT interval with the day-night difference in the HF to HF+LF power ratio of the heart rate variability parameters HF (high frequency) and LF (low frequency) power. Pharmacological studies of the autonomic contribution to QT agree that atropine reduces QT, while propranol and isoproterenol produce no changes [Ahnve 1982, Browne 1983b, LeCocq 1989, Cappato 1991]. Studies contrasting exercise and artificial pacing have shown that QT shortening in exercise is greater than that produced by heart rate increase alone, a difference attributed to changes in autonomic tone [Rickards 1981, Davey 1999]. Finally, two studies using heart transplant patients found that transplanted (anatomically denervated) hearts displayed blunted or absent day-night difference in QT [Bexton 1986, Alexopoulos 1988]. Alexopoulos et al also noted that transplanted hearts had shorter QT over 24 hour periods and during sleep, compared to control, but not during wake periods. To summarize autonomically induced hysteresisCIRC in man, studies in man largely agree in suggesting that QT is prolonged by vagal activation, and that some QT shortening is produced by circulating catecholamines.
The presence of heart rate change induced hysteresisVAR and autonomically induced hysteresisCIRC both complicate QT/RR slope measurement. In trying to deal with the problem of measuring variable slope caused by circadian hysteresisCIRC, some investigators have chosen to measure QT/RR slope separately for day vs. night. These studies are in agreement that QT/RR slope is greater during the day than at night [Coumel 1995, Anselme 1996, Extramiana 1999b]. To deal with hysteresisVAR, some investigators analyze only the portions of the QT/RR plot where heart rate has not changed for several minutes [Badilini 1998, Aytemir 1999]. There have also been attempts to quantify hysteresisVAR using computationally sophisticated techniques. One method computes the lag time between RR and QT change and effectively measures the slope after the QT has been shifted by that lag time [Neilson 2000, Lang 2001]. To use a crude example, if QT takes 3 seconds to adjust to a new heart rate of 100 bpm, one plots the QT 3 seconds after the heart rate change against the 100 bpm heart rate, instead of all the QT values traversed while adjusting to the new heart rate. The other method produces two values to characterize the temporal adaptation of QT to changes in heart rate, Lag, which describes time in seconds that RR intervals influence later QT values (140 sec on average, range 2-215 sec), and Lambda, a time constant of QT adaptation (average 48+/−8 beats) [Pueyo 2003].
In contrast to these many studies by clinician scientists who have been studying the relation between QT interval and SCD over many decades spurred by clinical experience, basic scientists have only over the last decade or so begun to show experimentally and theoretically, that the slope of action potential duration plotted against heart rate is closely coupled to arrhythmogenesis [Chialvo 1990, Watanabe 1995, Riccio 1999, Garfinkel 2000]. Action potential duration is the in vitro surrogate of the QT interval, and the term repolarization can be employed to refer to both QT interval and action potential duration. Nevertheless, basic scientists have produced many insights and predictions that could advance the field of repolarization parameter based SCD risk prediction. However, despite the clinical progress that might be made applying such knowledge, focused attempts to reconcile clinical data and specific experimental and theoretical results in a 1:1 fashion by scientists on either side of the clinical/basic scientist divide are thus far lacking. Articles in publications on the two sides of the divide generally lack even citations to studies by the other side, much less collaborative efforts. For instance, Holter ECG data in man (i.e. clinically oriented data compilation) is rarely collected to match experimental conditions (which would be considered to be standard procedure from a basic scientist perspective). A typical patient eats, sleeps, moves, takes medications, has various co-morbidities, and their heart rate changes to account for metabolic needs. In animal experiments, repolarization related data is measured with carefully planned stimulation protocols that absolutely control heart rate, with rare exceptions [Lux 2003]. Nevertheless, the inability of previous QT studies to produce definitive risk predictors with large hazard ratios suggest that interdisciplinary research and dialogue is necessary. It is perhaps telling that the best known and successful application of basic science knowledge to non-invasive risk prediction in recent years has been the use of T wave alternans to predict arrhythmia susceptibility. Perhaps this exception to the prevailing rule is because Dr. David Rosenbaum, a key investigator in this field, has been conducting both of the clinical and basic science studies necessary to realize the potential of the basic science findings.
In animals, Dr. Peng-Sheng Chen's group recently succeeded in recording autonomic nerve activity directly from sympathetic and vagal nerves using telemetry in conscious dogs, before and after heart failure induction by pacing. In their study, they found that integrated sympathetic nerve activity, though not vagal activity, showed significant circadian variations using cosinor analysis [Ogawa 2007]. These results give further support to the hypothesis that hysteresisCIRC of QT is caused by circadian variations in autonomic tone. In the past, before Dr. Chen's recent success with direct autonomic nerve recordings, demonstration of the effects of autonomic tone on QT relied on interpreting the effects that stimulating or cutting autonomic nerves had on repolarization properties in animal models. Two early studies found left sided sympathetic nerve stimulation to increase QT interval [Yanowitz 1966, Schwartz 1975], whereas two later studies found that effective refractory period, a surrogate measure of QT, decreased [Martins 1980, Inoue 1987]. Use of different anesthetics in these studies were suggested as a possible reason for the contradictory findings [Zaza 1991]. However, Opthof et al who used ventricular fibrillation interval as an index of local refractoriness, found that although the most common response to stellate ganglion stimulation was shortening of the ventricular fibrillation interval, some sites showed prolongation, the response was variable from dog to dog, depended on location in the ventricle, and whether the left or right stellate ganglion was stimulated [Opthof 1991]. In other words, just as left/right dominance of coronary arteries varies from individual to individual, Opthofs results suggested that there was no universal pattern of innervation of the ventricles by the left or right sided sympathetic nerves.
However, the inconsistent results of sympathetic stimulation on QT values could again indicate the nonlinear heart rate dependence of measures of repolarization (including QT interval, effective refractory period, or ventricular fibrillation interval) that present difficulties in interpreting animal study results. This property makes it difficult to ‘compare’ and conclude whether autonomic stimulation or removal has altered repolarization duration without fixing the heart rate. All of the studies cited above controlled heart rate by pacing, or in the case of the Inoue study, by titration of sympathetic and vagal stimulation to achieve the same heart rate. Zaza et al [1991] tried to circumvent this problem by fitting the action potential duration vs RR interval relationship to a hyperbolic function. Their results (see their FIG. 4) show the left and bilateral stellectomy curves intersecting the control curve, and thereby give visual proof that left stellectomy decreases action potential duration at short RR intervals, increases it at long RR intervals, and doesn't change it at the RR interval at which the curves intersect. In other words, the study of Zaza et al demonstrates that although fixing heart rate is better than comparing repolarization measures at different heart rates, it still fails to give the whole story. The intersecting curves may explain the contradictory results of left stellectomy effect on QT interval by different researchers, better than arguments about the kind of anesthetic that was used. So again, the Zaza results emphasize the importance of analyzing the QT/RR interval relationship as a whole, such as by Lissajous analysis, rather than for a proscribed segment.
Given the extreme negative consequences (unnecessary SCD) of errors in underutilizing defibrillator implantation, as well as the massive costs (unnecessary surgical risk, discomfort, and wasted billions of dollars in medical expenditures) incurred with the present treatment protocol, it is abundantly evident that improved means to accurately forecast risk of SCD are desirable.